Open AccessOptimization of Machining Characteristics of Hybrid Composites Using Grey Relational Technique
Author(s) -
G Ramanan.,
Neela Rajan.R.R,
Jai Aultrin. K. S,
P.V. Pradeep
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.1.17077
Subject(s) - machining , grey relational analysis , materials science , aluminium , composite number , rigidity (electromagnetism) , composite material , response surface methodology , aluminium alloy , alloy , computer science , mathematics , metallurgy , mathematical economics , machine learning
Metal matrix composite imparts several advantages over alloys. The MMCs exhibit improved properties compared with monolithic alloy. They are particularly suited for applications that require higher strength, dimensional stability and enhanced structural rigidity. Aluminium composite materials are engineered materials made from at least two or more constituent materials having different physical or chemical properties. In this work Seventeen turning experiments were conducted using response surface methodology. The machining parameters cutting speed, feed rate, and depth of cut are varied with respect to different machining conditions for each run. The optimal parameters were predicted by grey relational analysis technique. The optimum process parameter predicted from RSM techniques is cutting speed 250m/min, feed rate 0.06mm and depth of cut 1.5mm are found.